mtgp1000

Part of the reason for the 2008 financial crash was loans made to people who would have traditionally been "redlined" (denied credit for legitimate reasons) after a federal push for more inclusive loaning. IIRC this was a big chunk of overrated securities and at the very least contributed to instability by increasing the nationwide average probability of default.

>"Male spaces"?! Since when are conferences male spaces, they are a freaking professional space and yes expecting men (and women) to act professionally is exactly what we should do.

Male spaces are any spaces that are predominantly occupied by men. It is an observational definition and does not imply that women are deliberately excluded.

>B*ll, to imply that men can't control themselves is just offensive to men. But I guess you're also a proponent that women should wear burkas to protect them from those men that can't control themselves. Funny how those "policies" are always to the detriment of the women, not the men who can't control themselves. So much for unequal strain.

No, I am not implying that men cannot control themselves. But it's possible that in unisex spaces, there is a much higher burden on men not to be men than there is on women to accommodate to the spaces they are entering (practically by force).

But I'm glad you brought up burkas, because I considered mentioning the fact that men and women have largely self segregated across time and culture; we seem to be taking our very modern experiment with diversity and inclusion as though history (and non western culture) has been unambiguously wrong.

My ultimate point is inclusiveness does not come without its own costs, and there's no guarantee that an environment re-emagined to be overly inclusive will overall accomplish it's initial goals with the same effectiveness. In fact some degree of implicit exclusivity is not only good, but necessary for many pursuits. In sports the differences (not just in performance, but strategy) between males and females are obvious - but we're just supposed to pretend that sexual dimorphism stops at the shoulders?

With unprecedented power comes unprecedented responsibility.

>The call shows how Silicon Valley millionaires, who have been coddled by the press and lauded as innovators and disruptors, fundamentally misunderstand the role of journalism the moment it turns a critical eye to their industry.

No, I would argue that journalists don't understand that their role requires objectivity, and that the whole industry is broken because it has been completely dominated by ideologues, top to bottom, who are blatantly pushing politics onto the masses.

Don't support BLM? Have legitimate criticism? Be prepared to be called out by "journalists" until you fall in line, if you don't get cancelled first. And let's be real, this has been the status quo regarding taboo topics for at least a decade.

Edit: would you all be downvoting if the same journalists were adding pro Trump spin to a sizable proportion (or majority, depending on the outlet) of non-editorial (but editorialized) media? I'm not going to support blatantly partisan writing by ostensibly neutral platforms simply because they represent my politics. We need objective news and the fact that it is impossible to be purely objective is not an excuse to deliberately pollute news articles and headlines with consistent agenda.

>As a white person I'm not worried about the police pointing guns at me when walking home with my kids in a nice neighborhood

8 unarmed black men died at the hands of police last year. In a country with tens of millions of police interactions every year. And proportionally the number of white people who died by cop is approximately the same.

What people are worried about right now is a mass hysteria manufactured by a slanted media determined to paint a picture which absolves blacks of any responsibility.

I'm more than willing to admit that yes, to some extent, discrimination/racism play a role in unequal outcomes. Are you willing to accept that personal choices have a far greater effect?

Does personal responsibility matter at all anymore?

>The police, prosecutors and juries will go after black people more harshly and more often

And blacks are more likely to commit the crimes in the first place, and more likely to reoffend. If you want to blame "systematic racism" or whatever the term of the day is, you need to paint the whole picture, because culturally inspired behavior (fuck the police!) leads to culturally inspired outcomes.

Tell me, do you believe that the justice system (excluding marital issues) is biased against men relative to women, since the incarceration ratio is like 9:1?

>I am reasonably sure that I have it slightly easier at conferences as a man because women do not hit on me

Can we acknowledge the fact that most men would be ecstatic to be hit on by a woman or two at a conference? Can we acknowledge that men and women are innately different? That forcing men to change their behavior significantly to accommodate for women in male spaces may in fact place unequal strain on men?

Edit: are we just going to deny the fact that men are biologically driven to reproduce and compete for women? That this is an instinctual urge that we are required to suppress? You don't solve problems by ignoring their sources.

I trained a useful neural network and prototyped a viable [failed] startup technology something like 4 years ago on a 1080ti with a mid range CPU. It was enough to get me meetings with a couple of the largest companies in the world.

Yeah it took 12-24 hours to do what I could login to AWS and accomplish in minutes with parallel GPUs...but practical solutions were already in reach. The primary changes now are buzz and possibly unprecedent rate of research progress.

This is good. I think the commoditization of college had profound negative effects on society. Historic trust in the academic system was abused in order to, at best, sell degrees to people who were unqualified for them, and at worst, to indoctrinate two generations of children (anything outside of STEM is heavily politically slanted - it's the long march through the institutions that the infamous Weather Underground spoke of).

If intelligence (and general ability) is truly normally distributed then you cannot award degrees to the majority of the population without lowering historic standards.

If you consider "organism" and "environment" to be separate systems which may exchange energy/entropy, would it be fair to suppose that living organisms dump entropy into their environments to maintain internal order?

I agree that this is a typically murky discussion since the concept of entropy for a complex organism gets pretty handwavy...

I'm supposing that an organism in "living" condition has many orders of magnitude fewer valid microstates than the same constituent atoms/molecules would have once life sustaining reactions cease and decomposition begins - there are only so many valid ways to assemble a given living being...

I would argue that what the author said is somewhat true, in that life can be roughly separated from nonlife by the observation that organisms do appear to tend toward less entropy in a universe where everything else seemingly does the opposite.

Genetically coded beings are orderly structures with far fewer microstates than their molecular constituents would likely contain otherwise. And we tend to make copies of ourselves, giving order to otherwise chaotic matter.

I think there's a profoundness in there, somewhere. Such a definition also solves the virus conundrum!

People are stuck at home now, unemployed, fearful about the present and future, and if opioids were legalized now I have no doubt that dependence and overdoses would surge. Most people fundamentally don't understand drugs or addiction.

Granted I personally believe drugs should be at least decriminalized but I'm well aware that there will be a cost and people have a right to be opposed.

If the last few months have taught me anything, it's that the average person really isn't capable of avoiding decisions that harm themselves and those around them with any consistency. Obviously we already have laws for murder and such but drugs also as it happens have a [lesser] external cost.

The worst is the implicit social shame when you tell people you would prefer to use something like signal or telegram to mitigate risk.

This shit is on literally every platform, it's inescapable, and at this point necessary to participate in society.

>Really? I'm pretty sure there are thousands of years of philosophical and religious traditions that teach something along the lines of "looking for happiness in the external world is a bad idea, instead try working on yourself"

The author is referring to the common man, whom we in the west have been conditioned to think much more highly of than is evidently deserved.

It should not be controversial to say that people by and large are ignorant.

I want a plug and play hardware interface that can handle digital and analog io in a hackable package, capable of running cpp (easy to compile for) and if possible python.

If there are convenient alternatives to rpi, especially if they're cheaper for comparable performance, I'm all ears!

I'm not responding to this comment, just pointing out for anyone reading, that this person knows very well that he and his buddies won't be waiting with a "challenge" for anyone who attempts to publicly criticize BLM or the movement, but instead with a likely doxxing and unpersonning.

What, you think because it's crowdsourced it isn't liable to bias? You think they're going to accept a PR which attempts to remove multiple incidents, for any reason?

Because the "first order" "data correlation" tools that we use (typical statistical measures like correlation coefficients, means, stddev, etc) are inadequate for capturing the critical correlations in the kind of large, real world data sets that ML is shining in right now.

One example, if you have a thousand dimensional data set, and 3+ of dimensions are correlated, but only for certain value ranges, to find something like that with classical statistics, you would need an intuition and some digging and even then you might not see it.

If you suitably prepare your data and throw it into an ML it's trivial. Think of ML as automation for statistical inference. Because all neural nets really do is learn complex, super multivariate probability statistics - down to individual pixel-pixel relationships, for image data.

Edit: I'll add that one other reason ML works so well is that parameters in nets can learn (and represent) complex functions which are impractical (if not impossible) with mathematical notation. Which is what most complex real life distributions probably actually look like. It's like the bridge between analog and digital math, a sort of topological compression, if that makes any sense

You don't see a difference between an ideological party which interns millions of people by ethnicity (among other glaring issues), and a corporation seeking profits from a video platform?

This isn't about some minor annoyance, I'm pointing out something I truly believe holds society back, though not necessarily to some major degree

How much literature has disappeared from history because certain languages or vernaculars fell out of use?

Hell, why do we even bother teaching classical English if it's just going to change, right? We should just let kids learn from their parents and media - no use being a prescriptivist!

And yes, I do believe that some languages and dialects are vastly more expressive and unambiguous than others, but I don't expect the average person to understand that. Ultimately we're all free to speak as we wish but don't shame me for trying to preserve the necessary consistency that makes language useful.

This isn't black or white. It's about slowing the inevitable, yes, but it increases the usefulness of text over time. Less of a probability of material, including scientific, being forgotten.

It's driven primarily by ignorance and it muddies communication, especially over time. We should maintain some degree of pressure against such unnecessary change.

Because it is a dangerous fallacy to presume that all peoples are simply replaceable. When you import people you import culture, and that potentially leads to friction.

You're underappreciating how much more we are doing with neural networks now. Image recognition, general purpose contextual searching, NLP, accelerated 3D modeling, abstract problem solving (applied derivatives of alphago and other RL), and we're on the cusp of image synthesis, music synthesis, news summarization, not to mention translation...

All of this powered by dozens of exotic architectures and hundreds of discovered tweaks and optimizations - we are finally digging into the iceberg of which research before the 10s only scratch the surface. That's not to discount the visionary work of the past!

But if you plotted some general measure of progress in this field, you would see an enormous discontinuity in the derivative starting sometime in the 10s with GPUs and the open source/open science initiatives.

For all the shit I give to Google and Facebook and FAANG in general, they absolutely brought immense good to society by democratizing practical general function approximators. If there aren't any major roadblocks ML will touch every aspect of our near future lives, much like the internet. There's just too much potential - the cutting edge is just hitting the industry, our tech is already proven and it goes far deeper than classifying cats and dogs or digits. This is real science and it's huge, and it's a fact that even the money has never been remotely there for the kind of progress we are making; not to even mention the drastic difference between running ML on 1980s hardware vs a modern GPU. The kind of science we can now do from the comfort of our homes was impossible until very recently.

It's like coming out of the bronze age and starting to work with steel. We build the tools as we go along. This is part of the process and we're actually doing a great job.

I feel like we are all ignoring the fact that literally any perceived disrespect can be blamed on racism, especially if you've been conditioned to look for it, and it's often impractical or impossible to prove otherwise, particularly once the mob has mobilized.

Being told you're a victim all your life can make you feel like a victim, even when you aren't. And now that victimhood is currency, all I see as a foreigner looking in is a growing unilateral justification for the oppression and deliberate marginalization of whites. Young white boys are already being left behind in school.

You don't solve oppression with oppression.

Yes, the foundations for ML are somewhat old, but the explosion of progress has put everyone on the edge of a fresh domain for which we are only now developing a theoretical framework.

At the very least you must concede that applied machine learning is effectively a new field. Yes I'm sure a handful of neuron-like components have probably been assembled here or there in the past to do something interesting, but no one was going to college trying to make it big with a career in ML.

>But it's not science

That's just not true. We are probing a novel domain.

In fact how else would you expect this to proceed? We've discovered a new phenomenon, which likely requires novel mathematics, yet through this exact kind of experimentation we are building the intuition that will guide more rigorous formalization later.

Sure, I get it, the quality on arxiv isn't the same as some physics journal; but to dismiss this as unscientific is not only wrong but very much unfair. I'm working the cutting edge at work, and we're documenting our discoveries as we map the structure of a new frontier - if that isn't science, I don't know what is.

tldr this is how science progresses in new domains before novel mathematics and formalisms are developed to address the new class of problems. This is a really exciting time if neural nets don't hit any serious blocks.

Edit: and by the way, my coworkers are all graduated educated scientists from various backgrounds. What else are they doing if not science?

>They may be useful in the sense of generating commercial value, just like ML is useful to random-walking you to some solution that you couldn't have come up with, but it is not science.

There is little insight to be gained from this, it is more guesswork and art than anything else, and likely at some points the practical results will diminish as soon as one stumbles about more fundamental problems and has no model or structure to reason with

This is just normal for the scientific process, and I'd argue that ML currently is more rigorous than any of the soft sciences. The truth is that we likely need a new field of math to properly model neural networks...until then we are gleaning vast amounts of empirical but still scientific data as to the behavior of this new tech.

The proof is that these nets work and are already doing amazing things.

>What does that tell us? A few things, first the authors are completely ignoring the danger of multiple hypothesis testing and generally piss on any statistical foundations of their "research"

This is a really poor take, considering I make the same gut feel choices professionally and they generally work in production.

This is still a brand new field and we fundamentally don't have answ re as to why many of these tweaks work better than others. That shouldn't stop someone from publishing a novel architecture or improvement.

At this point, what are the odds that the Chinese government isn't involved in tiktok?